PLC Research

Power Line Communications (PLC) is a new exciting field of research and development where spectral efficient, reliable communication schemes are realized over existing wires. Application scenarios include in-home (low voltage), outdoor (low, medium and high voltage), and in-vehicle (car, ship, airplane).

In our lab we are devoloping and testing transmission schemes based on Filter Bank Modulation, and Impulsive UWB Modulation.
We are also working on developing channel models and sofware simulators that can help developing and testing new and existing transmisision technologies. We are following both a top-down statistical channel model approach and a bottom-up approach.

Advanced Multitone Technology for PLC

We have developed a novel breakthrough filter bank technology that captures the best charactersitics of the known filter bank solutions but in a radical new architetural philosophy. It exhibits high performance in nasty channels, yet requiring an efficient low complexity implementation. Targeted applications are wireless, wireline and power line communications.

If you are working in enhancing current technology, or you have in mind nice application scenarios, or you are seeking for novel high performance transmission solutions, please contact A. Tonello at tonello@uniud.it.

UWB for Power Line Communications

UWB in the form of impulsive modulation is an interesting transmission technique for its low implementation complexity. We are investigating it both for in-home and smart-grid applcations.

Measurement and Characterization of the PLC channel

Channel measurements are improtant to characterize the PLC channel. We have developed both measurement methodologies and statistical analysis tools.

New results about the characterization of the in’home PLC channel can be found in [R0].

A Matlab code (Release 1.0) to analyse data according to [R0] can be downloaded at the link below. The script computes the channel impulse response (CIR), the average channel gain (ACG), the RMS delay spread, and the deterministic coherence bandwidth at level 0.9 of the channel frequency response H defined at frequencies f. For further details, see [R0].

Top-down PLC Channel Modeling and Generator

Top-down channel modeling refers to an approach where the channel impulse/frequency response is obtained with a parametric model with parameters obtained by fitting real data from measurements. Instead of using a deterministic top-down model, we are working on a statistical model. The statistical top-down model allows generating channels with statistics identical to those exhibited by real channels. In particular, the model is simple, flexible, and it uses a small set of parameters. The parameters can be adjusted to generate channel according to a certain statistical class. For instance, we can classify channels according to their average path-loss, gain, delay spread, and capacity.

The idea of statistical top-down modeling was originally presented in:

A Matlab code (Release 1.0) and updates (Release 2.0, according to [R3] and Release 3.0, according to [R4]) can be downloaded at the links below.

Copyright: A. M. Tonello. Notice: This software is freely usable for non commercial activities provided that [R1] and [R4] are cited and this web link is reported. Any use has to comply with the copyright terms. Any modification and/or commercial use has to be authorized by the copyright owner.

Bottom-up PLC Channel Modeling and Generator

Bottom-up channel modeling refers to an approach where the channel impulse/frequency response is obtained via the application of transmission line (TL) theory to a specified network topology, cables and loads characteristics. Conventionally, this approach is applied to obtain a specific response and it is also referred to as deterministic model. Further, for complex networks the existing calculation methods are rather complex.
We have extended this idea in order to obtain an accurate statistical channel generator. This has been obtained by developing a realistic statistical description of in-home topologies. To overcome the computational effort in obtaing the channel responses, we have devised an efficient method for the computation of the channel transfer function.